The Holiday marketing playbook is broken. Here’s how to fix it with AI agents.

Black Friday and Cyber Monday (BFCM) used to be a single weekend of frenzied shopping. Today, the peak shopping season often spans a full week—and in many cases, the entire month of November—as brands launch campaigns early and extend them well beyond the big days.

For retailers, this window often makes or breaks annual revenue targets each year and its importance is only growing. In 2024, U.S. holiday sales reached $241.4 billion, nearly $20 billion more than the year before. For marketers, that means months of grueling preparation building out send calendars, writing clever subject lines, creating enticing offers, and competing for attention in the noisiest promotional period of the year.

And yet, despite all the effort, results still fall short. Traditional marketing strategies built on batch sends and rigid journeys simply can’t keep up with how customers actually shop.

Why the old playbook is broken

Traditional holiday marketing was designed for a simpler time. The formula of blasting out big discounts to large segments on fixed dates worked when shoppers had fewer choices and weren't drowning in promotional emails. But today's reality is quite different.

BFCM has evolved into a messaging arms race. Brands compete on deeper discounts, flashier subject lines, and increasingly aggressive send frequencies. The result? Eroded profit margins, overwhelmed customers, and diminishing returns on marketing spend.

Everyone's shouting louder, but fewer people are listening.

Even sophisticated marketers using advanced segmentation, dynamic content and A/B testing can only optimize a tiny fraction of the variables that influence individual consumer purchase behavior. Your batch campaign might hit a night owl at 9 AM when they're rushing to work, or reach a bargain hunter with full-price messaging when they're waiting for deeper discounts. A loyal customer gets the same generic "50% off everything!" email as someone who's never purchased before. The combinatorial complexity quickly becomes impossible to manage manually at scale.

The cost of this one-size-fits-most approach compounds during peak season, when every missed opportunity represents significant revenue loss and customer attention is at its scarcest.

Flipping the paradigm: From reach to precision with AI agents

Winning retailers this holiday season aren’t sending more messages, they’re making every message smarter. With AI agents, every decision—from the offer to the creative to the timing and channel—is personalized at the individual level.

This is the shift from manual campaigns to continuous optimization. AI Decisioning platforms power that shift by replacing rigid calendars and endless A/B tests with AI agents that use reinforcement learning to adapt in real time and maximize outcomes.

For marketers, that means:

• No more guessing which segments to target on which days
• No more manually mapping journeys for millions of customers
• No more blanket discounts that shrink margins without adding value

AI agents unlock a new paradigm of “agentic marketing”

How AI Decisioning works

AI Decisioning begins with the end in mind—asking marketers to first define the business goals they want to achieve (like driving cross-sells or increasing LTV) and then uses AI agents to find the best path to conversion for each individual.

After defining their goals, marketers supply content, creative, and guardrails as inputs for the agent. From there, AI agents autonomously evaluate each customer’s context in real time and select the best combination of content, timing, and delivery.

Marketers create an agent directly in Hightouch by first defining their business goals

The result? Marketers finally get to focus on strategy and creativity, while AI handles the complexity of personalization at scale—all during the most critical shopping period of the year.

This is exactly what we've built at Hightouch with our AI Decisioning platform. Our AI Decisioning platform connects directly to your existing customer data warehouse and the marketing platforms that you already use, so you can get set up quickly, without redoing your entire marketing workflow, uploading content, or rearchitecting your tools.

Hightouch connects directly to your data warehouse and integrates with any marketing platform

Real-world use cases

Here are a few practical applications for BFCM:

• Cross-sell and upsell agents: A customer who snagged a 55" TV during your Black Friday doorbuster might immediately see a personalized offer for a discounted soundbar, but only because the AI knows similar BFCM electronics buyers convert 3x higher on audio accessories within 48 hours. The agent times the follow-up perfectly, hitting them Tuesday morning when post-purchase excitement peaks, through their preferred channel.
• Winback and re-engagement agents: Those BFCM bargain hunters who went dark after Cyber Monday? Instead of generic January "we miss you" emails, AI Decisioning crafts recovery strategies based on their holiday shopping behavior. A customer who bought luxury skincare during BFCM gets a curated "New Year, New You" collection, while the deal-seeker who only bought during your deepest discounts gets a flash sale alert when they display browsing intent.
• Recurring purchase agents: Holiday shopping is an opportunity to turn one-time buyers into repeat customers. AI sees a shopper picked up multiple bags during your BFCM sale and nudges them back in mid-December with a refill offer, converting seasonal stock-ups into recurring visits.
• Offer recommendation agents: During BFCM chaos, most brands blast the same 30% off deal to everyone. AI Decisioning can help recognize your points-obsessed loyalty members will jump on a "2X points on all Black Friday purchases" offer, while the cash-conscious customers respond to "Buy 2, Get 1 Free" on items to increase conversions.

Each use case taps into robust customer data available in the warehouse to power 1:1 personalization beyond human scale. Instead of building rigid journeys, marketers set the outcomes, and AI agents decide the best way to achieve them for every customer.

Leading brands are already making the shift

This isn’t just theory. Leading brands are already seeing results. WHOOP, the health and fitness wearable brand, spent over a year trying to grow cross-sells in apparel and accessories with limited success. In less than two months of implementing AI Decisioning, their lifecycle team saw a 10% increase in cross-sell conversions. Even better, AI surfaced insights about low-propensity audiences about customers previously unreachable, unlocking new growth opportunities.

The future of peak season marketing

Lifecycle marketing is no longer about flooding inboxes or guessing which combinations of offers and creative will resonate. It’s about precision, personalization, and profitable growth. With AI Decisioning, marketers can finally break free from the stressful cycle of manual planning and endless testing. Instead, they can deploy an agentic intelligence layer that enhances their existing marketing tools that puts real personalization within reach.

This peak season, the retailers that embrace AI will turn their biggest challenge into their biggest opportunity, and exceed their revenue goals in the process.

Want to explore how this could work for your business? Book some time with our team.